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CHAPTER 7

CHAPTER 7. INTRODUCTION TO OBJECTS. Overview. What is a module? Cohesion Coupling Data encapsulation product maintenance Abstract data types Information hiding Objects Inheritance, polymorphism and dynamic binding Cohesion and coupling of objects. Introduction to Objects.

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CHAPTER 7

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  1. CHAPTER 7 INTRODUCTION TO OBJECTS

  2. Overview • What is a module? • Cohesion • Coupling • Data encapsulation product maintenance • Abstract data types • Information hiding • Objects • Inheritance, polymorphism and dynamic binding • Cohesion and coupling of objects

  3. Introduction to Objects • What is a module? • A lexically contiguous sequence of program statements, bounded by boundary elements, with an aggregate identifier (name)

  4. Design of Computer • A highly incompetent computer architect decides to build an ALU, shifter and 16 registers with AND, OR, and NOT gates, rather than NAND or NOR gates.

  5. Design of Computer (contd) • Architect designs 3 silicon chips

  6. Design of Computer (contd) • Redesign with one gate type per chip • Resulting “masterpiece”

  7. Computer Design (contd) • The two designs are functionally equivalent • Second design is • Hard to understand • Hard to locate faults • Difficult to extend or enhance • Cannot be reused in another product • Modules must be like the first design • Maximal interactionswithin modules, minimal interactions between modules

  8. Composite/Structured Design (C/SD) • Method for breaking up a product into modules for • Maximal interaction within module, and • Minimal interaction between modules • Module cohesion • Degree of interaction within a module • Module coupling • Degree of interaction between modules High Cohesion but Low Coupling is desirable

  9. Action, Logic, and Context of Module • The action of a module – what it does • The logic of a module – how the module performs its action • The context of a module is the specific usage of that module • In C/SD, the name of a module is its action • Example • Module computes square root of double precision integers using Newton’s algorithm. Module is named compute square root

  10. Cohesion • The degree of interaction within a module • Seven categories or levels of cohesion • Functional cohesion is optimal for the structured paradigm • Informational cohesion is optimal for OO paradigm

  11. 1. Coincidental Cohesion • A module has coincidental cohesion if it performs multiple, completely unrelated actions • Example • print next line, reverse string of characters comprising second parameter, add 7 to fifth parameter, convert fourth parameter to floating point • Arise from rules like • “Every module will consist of between 35 and 50 statements”

  12. Why Is Coincidental Cohesion So Bad? • Degrades maintainability • Modules are not reusable • This is easy to fix • Break into separate modules each performing one task

  13. 2. Logical Cohesion • A module has logical cohesion when it performs a series of related actions, one of which is selected by the calling module • Example 1 function code = 7; new operation (op code, dummy 1, dummy 2, dummy 3); // dummy 1, dummy 2, and dummy 3 are dummy variables, // not used if function code is equal to 7 • Example 2 • Module performing all input and output • Example 3 • One version of OS/VS2 contained logical cohesion module performing 13 different actions. Interface contained 21 pieces of data

  14. Why Is Logical Cohesion So Bad? • The interface is difficult to understand • Code for more than one action may be intertwined, leading to maintenance problems • Difficult to reuse

  15. Why Is Logical Cohesion So Bad? (contd) • Example: If a new tape unit is installed, what sections of code should be modified?

  16. 3. Temporal Cohesion • A module has temporal cohesion when it performs a series of actions related in time • Example • open old master file, new master file, transaction file, print file, initialize sales district table, read first transaction record, read first old master record (a.k.a. perform initialization)

  17. Why Is Temporal Cohesion So Bad? • Actions of this module are weakly related to one another, but strongly related to actions in other modules. • Consider sales district table • Not reusable

  18. 4. Procedural Cohesion • A module has procedural cohesion if it performs a series of actions related by the procedure to be followed by the product • Example • read part number and update repair record on master file

  19. Why Is Procedural Cohesion So Bad? • Actions are still weakly connected, so module is not reusable

  20. 5. Communicational Cohesion • A module has communicational cohesion if it performs a series of actions related by the procedure to be followed by the product, but in addition all the actions operate on the same data • Example 1 • update record in database and write it to audit trail • Example 2 • calculate new coordinates and send them to terminal

  21. Why Is Communicational Cohesion So Bad? • Still lack of reusability

  22. 7. Informational Cohesion • A module has informational cohesion if it performs a number of actions, each with its own entry point, with independent code for each action, all performed on the same data structure

  23. Why Is Informational Cohesion So Good? • Essentially, this is an abstract data type • Optimal for the OO paradigm

  24. 7. Functional Cohesion • Module with functional cohesion performs exactly one action • Example 1 • get temperature of furnace • Example 2 • compute orbital of electron • Example 3 • write to floppy disk • Example 4 • calculate sales commission

  25. Why is functional cohesion so good? • More reusable • Corrective maintenance easier • Fault isolation • Fewer regression faults • Easier to extend product

  26. Cohesion Case Study

  27. Coupling • Degree of interaction between two modules • Five categories or levels of coupling

  28. 1. Content Coupling • Two modules are content coupled if one directly references contents of the other • Example 1 • Module a modifies statement of module b • Example 2 • Module a refers to local data of module b in terms of some numerical displacement within b • Example 3 • Module a branches into local label of module b

  29. Why Is Content Coupling So Bad? • Almost any change to b, even recompiling b with new compiler or assembler, requires change to a

  30. 2. Common Coupling • Two modules are common coupled if they have write access to the same global data • Example 1 • Modules cca and ccb can access and change value of global variable

  31. 2. Common Coupling (contd) • Example 2 • Modules cca and ccb both have access to same database, and can both read andwrite same record • Example 3 • FORTRAN common • COBOL common (nonstandard) • COBOL-80 global

  32. Why Is Common Coupling So Bad? • Contradicts the spirit of structured programming • The resulting code is virtually unreadable

  33. Why Is Common Coupling So Bad? (contd) • Modules can have side effects • This affects their readability • If a maintenance change is made to a global data in a module then every module that can access that global data has to be changed • Difficult to reuse • Module exposed to more data than necessary

  34. 3. Control Coupling • Two modules are control coupled if one passes an element of control to the other • Example 1 • Operation code passed to module with logical cohesion • Example 2 • Control-switch passed as argument

  35. Why Is Control Coupling So Bad? • Modules are not independent; module b (the called module) must know internal structure and logic of module a. • Affects reusability • Associated with modules of logical cohesion

  36. 4. Stamp Coupling • Some languages allow only simple variables as parameters • part number • satellite altitude • degree of multiprogramming • Many languages also support passing of data structures • part record • satellite coordinates • segment table

  37. 4. Stamp Coupling (contd) • Two modules are stamp coupled if a data structure is passed as a parameter, but the called module operates on some but not all of the individual components of the data structure

  38. Why Is Stamp Coupling So Bad? • It is not clear, without reading the entire module, which fields of a record are accessed or changed • Example calculate withholding (employee record) • Difficult to understand • Unlikely to be reusable • More data than necessary is passed • Uncontrolled data access can lead to computer crime • There is nothing wrong with passing a data structure as a parameter, provided all the components of the data structure are accessed and/or changed e.g., - invert matrix (original matrix, inverted matrix) - print inventory record (warehouse record)

  39. 5. Data Coupling • Two modules are data coupled if all parameters are homogeneous data items (simple parameters, or data structures all of whose elements are used by called module) • Examples • display time of arrival (flight number) • compute multiplication (first number, second number, result) • get job with highest priority (job queue)

  40. Why Is Data Coupling So Good? • The difficulties of content, common, control, and stamp coupling are not present • Maintenance is easier

  41. Coupling Case Study

  42. Coupling Case Study (contd) • Interface description

  43. Coupling Case Study (contd) • Coupling between all pairs of modules

  44. Data Encapsulation • Example • Design an operating system for a large mainframe computer. It has been decided that batch jobs submitted to the computer will be classified as high priority, medium priority, or low priority. There must be three queues for incoming batch jobs, one for each job type. When a job is submitted by a user, the job is added to the appropriate queue, and when the operating system decides that a job is ready to be run, it is removed from its queue and memory is allocated to it. • Design 1 (Next slide) • Low cohesion—operations on job queues are spread all over product

  45. Data Encapsulation — Design 1

  46. Data Encapsulation — Design 2

  47. Data Encapsulation • m_encapsulation has informational cohesion • m_encapsulation is an implementation of data encapsulation • Data structure (job_queue) together with operations performed on that data structure • Advantages of using data encapsulation • Development • Maintenance

  48. Data Encapsulation and Development • Data encapsulation is an example of abstraction • Job queue example • Data structure • job_queue • Three new functions • initialize_job_queue • add_job_to_queue • delete_job_from_queue • Abstraction • Conceptualize problem at higher level • job queues and operations on job queues • not lower level • records or arrays

  49. Stepwise Refinement 1. Design in terms of high level concepts • It is irrelevant how job queues are implemented 2. Design low level components • Totally ignore what use will be made of them • In 1st step, assume existence of lower level • Concern is the behavior of the data structure • job_queue • In 2nd step, ignore existence of high level • Concern is the implementation of that behavior • In a larger product, there will be many levels of abstraction

  50. Data Encapsulation and Maintenance • Identify aspects of product likely to change • Design product so as to minimize the effects of change • Data structures are unlikely to change • Implementation may change • Data encapsulation provides a way to cope with change

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